Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods or our paper for further explanation).

Using data available up to the: 2020-06-22

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-06-11) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-06-11 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-06-11)

Table 1: Latest estimates (as of the 2020-06-11) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Afghanistan 643 (582 – 694) Unsure 1 (0.9 – 1.1) 340 (41 – -54)
Albania 61 (45 – 75) Likely increasing 1.2 (1 – 1.4) 15 (6.9 – -96)
Algeria 123 (102 – 144) Likely increasing 1.1 (0.9 – 1.2) 39 (13 – -40)
Andorra 5 (0 – 14) Unsure 1.4 (0.1 – 3) 4 (1 – -2.7)
Argentina 1648 (1467 – 1814) Increasing 1.2 (1.1 – 1.2) 16 (13 – 22)
Armenia 572 (521 – 630) Increasing 1.1 (1 – 1.1) 36 (19 – 260)
Australia 21 (11 – 29) Likely increasing 1.4 (1 – 1.8) 7.8 (3.8 – -70)
Austria 35 (23 – 45) Unsure 1.1 (0.9 – 1.4) 22 (6.8 – -17)
Azerbaijan 394 (347 – 442) Increasing 1.1 (1 – 1.2) 31 (16 – 560)
Bahrain 490 (435 – 541) Unsure 1 (0.9 – 1.1) -190 (48 – -32)
Bangladesh 3640 (3356 – 3907) Increasing 1.1 (1.1 – 1.1) 29 (22 – 40)
Belarus 709 (641 – 764) Likely decreasing 1 (0.9 – 1) -99 (87 – -32)
Belgium 98 (76 – 114) Likely decreasing 0.9 (0.8 – 1.1) -36 (37 – -12)
Benin 41 (28 – 52) Increasing 1.3 (1 – 1.7) 9.1 (4.7 – 86)
Bolivia 873 (784 – 957) Increasing 1.2 (1.1 – 1.2) 18 (13 – 27)
Bosnia and Herzegovina 60 (44 – 74) Likely increasing 1.2 (1 – 1.4) 20 (7.8 – -35)
Brazil 32653 (29114 – 35649) Increasing 1.1 (1.1 – 1.2) 23 (18 – 31)
Bulgaria 94 (73 – 108) Likely increasing 1.1 (1 – 1.3) 32 (11 – -35)
Cameroon 273 (228 – 315) Unsure 1.1 (0.9 – 1.2) 67 (17 – -34)
Canada 402 (358 – 450) Likely decreasing 0.9 (0.8 – 1) -43 (120 – -18)
Central African Republic 97 (80 – 115) Unsure 1.1 (0.9 – 1.2) 39 (11 – -28)
Chad 4 (0 – 8) Unsure 1.1 (0.2 – 2) 13 (2 – -3.1)
Chile 10315 (9536 – 11290) Increasing 1.3 (1.2 – 1.3) 11 (9.3 – 13)
China 41 (28 – 51) Increasing 1.4 (1.1 – 1.7) 7.2 (4 – 28)
Colombia 2525 (2310 – 2768) Increasing 1.2 (1.2 – 1.3) 12 (10 – 15)
Congo 34 (22 – 43) Increasing 1.3 (1 – 1.6) 10 (4.8 – -95)
Costa Rica 72 (53 – 87) Likely increasing 1.1 (1 – 1.3) 24 (9 – -36)
Cote dIvoire 284 (254 – 313) Increasing 1.2 (1 – 1.3) 18 (11 – 50)
Croatia 9 (3 – 15) Increasing 1.9 (1 – 2.9) 3.6 (1.8 – 170)
Cuba 14 (5 – 21) Unsure 1.1 (0.7 – 1.6) 24 (4.6 – -7.8)
Czechia 71 (53 – 88) Likely increasing 1.1 (0.9 – 1.3) 24 (8.9 – -34)
Democratic Republic of the Congo 142 (120 – 165) Likely increasing 1.1 (1 – 1.2) 31 (12 – -58)
Denmark 39 (27 – 49) Unsure 1.1 (0.8 – 1.3) 28 (8 – -18)
Djibouti 24 (12 – 33) Decreasing 0.7 (0.4 – 0.9) -9 (280 – -4.4)
Dominican Republic 500 (435 – 548) Increasing 1.1 (1 – 1.1) 45 (21 – -260)
Ecuador 607 (549 – 659) Increasing 1.1 (1 – 1.1) 35 (19 – 220)
Egypt 1621 (1504 – 1751) Increasing 1.1 (1 – 1.1) 44 (27 – 120)
El Salvador 146 (125 – 167) Increasing 1.2 (1 – 1.3) 16 (9.1 – 78)
Equatorial Guinea 54 (36 – 72) Increasing 2 (1.5 – 2.6) 2.9 (2.1 – 4.8)
Estonia 4 (0 – 9) Unsure 0.9 (0.3 – 1.5) -9.8 (4.3 – -2.4)
Ethiopia 194 (167 – 215) Likely increasing 1.1 (1 – 1.2) 56 (17 – -46)
Finland 10 (4 – 16) Likely decreasing 0.8 (0.5 – 1.2) -11 (13 – -3.9)
France 517 (449 – 576) Likely increasing 1.1 (1 – 1.1) 32 (17 – 220)
Gabon 137 (112 – 156) Increasing 1.2 (1.1 – 1.4) 11 (6.7 – 26)
Germany 528 (449 – 597) Increasing 1.2 (1.1 – 1.3) 13 (9.3 – 21)
Ghana 352 (308 – 393) Increasing 1.1 (1 – 1.2) 21 (13 – 60)
Greece 24 (14 – 33) Unsure 1.1 (0.8 – 1.4) 59 (6.6 – -8.8)
Guatemala 499 (448 – 556) Increasing 1.1 (1.1 – 1.2) 20 (13 – 42)
Guinea 72 (56 – 88) Likely increasing 1.1 (0.9 – 1.3) 21 (8.7 – -49)
Guinea Bissau 17 (8 – 23) Unsure 1.2 (0.8 – 1.6) 13 (4.5 – -14)
Haiti 132 (111 – 152) Unsure 1 (0.8 – 1.1) -58 (33 – -15)
Honduras 559 (476 – 631) Increasing 1.3 (1.2 – 1.4) 11 (8.6 – 16)
Hungary 7 (2 – 11) Likely decreasing 0.8 (0.4 – 1.2) -9.3 (10 – -3.2)
Iceland 5 (0 – 8) Likely increasing 2 (0.5 – 3.3) 3.3 (1.4 – -7.2)
India 13428 (12292 – 14526) Increasing 1.1 (1.1 – 1.2) 22 (19 – 26)
Indonesia 1151 (1043 – 1260) Increasing 1.1 (1 – 1.2) 31 (20 – 65)
Iran 2636 (2430 – 2830) Increasing 1.1 (1 – 1.1) 32 (23 – 52)
Iraq 1512 (1360 – 1679) Increasing 1.2 (1.1 – 1.2) 18 (14 – 27)
Ireland 15 (7 – 21) Unsure 1 (0.6 – 1.3) 76 (6.4 – -7.6)
Israel 243 (204 – 279) Increasing 1.2 (1.1 – 1.3) 16 (9.9 – 42)
Italy 266 (233 – 293) Unsure 1 (0.9 – 1.1) 440 (28 – -32)
Japan 55 (40 – 67) Likely increasing 1.1 (0.9 – 1.3) 24 (8.4 – -27)
Kazakhstan 403 (355 – 455) Increasing 1.2 (1.1 – 1.3) 14 (9.6 – 23)
Kenya 148 (125 – 170) Likely increasing 1.1 (0.9 – 1.2) 36 (13 – -48)
Kosovo 40 (28 – 51) Likely increasing 1.3 (1 – 1.6) 11 (5.4 – -92)
Kuwait 557 (491 – 608) Unsure 1 (0.9 – 1.1) -140 (52 – -30)
Kyrgyzstan 124 (104 – 144) Increasing 1.4 (1.1 – 1.6) 7.7 (5.2 – 14)
Latvia 6 (0 – 11) Likely increasing 1.6 (0.5 – 2.7) 5.1 (1.8 – -5.9)
Lebanon 16 (7 – 23) Unsure 1 (0.7 – 1.4) 380 (7 – -7.2)
Libya 18 (8 – 25) Unsure 0.9 (0.6 – 1.2) -17 (13 – -5.1)
Lithuania 8 (2 – 13) Unsure 1.1 (0.5 – 1.5) -100 (4.8 – -4.4)
Luxembourg 9 (3 – 14) Likely increasing 1.4 (0.7 – 1.9) 8.7 (2.9 – -9.2)
Madagascar 39 (26 – 50) Unsure 1.1 (0.8 – 1.3) 38 (7.9 – -14)
Malawi 19 (11 – 27) Unsure 1.1 (0.8 – 1.4) 19 (5.4 – -12)
Malaysia 20 (11 – 27) Likely decreasing 0.8 (0.5 – 1) -29 (11 – -6.5)
Maldives 26 (15 – 35) Unsure 1.1 (0.8 – 1.4) 19 (6 – -16)
Mali 25 (15 – 35) Likely decreasing 0.8 (0.6 – 1.1) -14 (31 – -5.7)
Mauritania 181 (154 – 203) Increasing 1.3 (1.1 – 1.4) 11 (7.2 – 22)
Mexico 4884 (4522 – 5348) Increasing 1.1 (1.1 – 1.1) 31 (24 – 43)
Moldova 386 (339 – 435) Increasing 1.2 (1.1 – 1.3) 16 (11 – 32)
Mongolia 5 (0 – 9) Likely increasing 1.9 (0.5 – 3.3) 3.2 (1.4 – -5.8)
Morocco 166 (139 – 194) Increasing 1.3 (1.2 – 1.5) 8.8 (6 – 16)
Nepal 457 (422 – 497) Increasing 1.1 (1 – 1.2) 21 (13 – 56)
Netherlands 139 (117 – 160) Likely decreasing 0.9 (0.8 – 1) -30 (81 – -13)
New Zealand 4 (0 – 8) Likely increasing 2.3 (0.3 – 4) 2.3 (1 – -4.7)
Niger 10 (3 – 15) Likely increasing 1.6 (0.8 – 2.3) 5.2 (2.3 – -26)
Nigeria 627 (560 – 700) Increasing 1.1 (1.1 – 1.2) 21 (14 – 43)
North Macedonia 163 (140 – 183) Likely increasing 1.1 (1 – 1.2) 42 (15 – -49)
Norway 18 (8 – 25) Unsure 1.1 (0.7 – 1.5) 36 (5.6 – -8.1)
Oman 965 (904 – 1039) Likely increasing 1.1 (1 – 1.1) 42 (23 – 270)
Pakistan 5800 (5475 – 6203) Increasing 1 (1 – 1.1) 66 (42 – 150)
Palestine 47 (32 – 60) Increasing 1.8 (1.4 – 2.3) 3.9 (2.7 – 7.3)
Panama 785 (701 – 864) Increasing 1.2 (1.1 – 1.2) 17 (13 – 27)
Paraguay 16 (7 – 22) Unsure 0.9 (0.6 – 1.2) -21 (11 – -5.4)
Peru 4062 (3855 – 4290) Decreasing 1 (0.9 – 1) -79 (-540 – -43)
Philippines 608 (541 – 675) Likely increasing 1.1 (1 – 1.1) 54 (23 – -140)
Poland 397 (356 – 439) Unsure 1 (0.9 – 1.1) -180 (41 – -28)
Portugal 357 (308 – 403) Likely increasing 1.1 (1 – 1.2) 37 (17 – -170)
Puerto Rico 116 (97 – 133) Unsure 1 (0.8 – 1.1) -520 (20 – -19)
Qatar 1275 (1182 – 1361) Decreasing 0.9 (0.9 – 1) -39 (-100 – -24)
Romania 306 (265 – 344) Increasing 1.2 (1.1 – 1.3) 14 (9.4 – 27)
Russia 8577 (8105 – 9165) Likely increasing 1 (1 – 1) 210 (82 – -340)
Saudi Arabia 4561 (4244 – 4933) Increasing 1.1 (1.1 – 1.2) 21 (18 – 27)
Senegal 111 (91 – 129) Unsure 1 (0.9 – 1.2) 97 (16 – -24)
Serbia 84 (65 – 100) Likely increasing 1.1 (0.9 – 1.3) 29 (10 – -36)
Sierra Leone 29 (18 – 39) Unsure 1.1 (0.8 – 1.3) 72 (8.2 – -11)
Singapore 259 (227 – 287) Decreasing 0.9 (0.8 – 0.9) -21 (-76 – -12)
Slovakia 8 (2 – 13) Likely increasing 1.6 (0.8 – 2.3) 6.1 (2.4 – -12)
Somalia 28 (18 – 38) Likely decreasing 0.9 (0.6 – 1.1) -17 (25 – -6.4)
South Africa 4005 (3676 – 4307) Increasing 1.2 (1.1 – 1.2) 17 (14 – 20)
South Korea 51 (36 – 63) Unsure 1.1 (0.9 – 1.3) 38 (9.3 – -18)
South Sudan 26 (16 – 35) Likely decreasing 0.8 (0.6 – 1) -10 (72 – -4.9)
Spain 368 (325 – 411) Likely increasing 1.1 (1 – 1.1) 30 (16 – 310)
Sri Lanka 14 (7 – 21) Unsure 1 (0.6 – 1.5) 29 (4.7 – -6.8)
Sudan 225 (198 – 250) Increasing 1.1 (1 – 1.2) 22 (12 – 170)
Sweden 845 (778 – 901) Likely decreasing 0.9 (0.9 – 1) -81 (83 – -27)
Switzerland 36 (22 – 45) Increasing 1.3 (1 – 1.6) 10 (5 – -1600)
Tajikistan 63 (47 – 76) Likely decreasing 0.9 (0.8 – 1.1) -40 (24 – -11)
Thailand 5 (1 – 10) Unsure 1.3 (0.4 – 2.1) 9.5 (2.3 – -4.6)
Tunisia 11 (4 – 17) Increasing 1.7 (0.9 – 2.4) 4.7 (2.3 – -97)
Turkey 1455 (1347 – 1555) Increasing 1.1 (1.1 – 1.2) 19 (14 – 28)
Uganda 13 (5 – 19) Unsure 0.9 (0.5 – 1.3) -21 (7.6 – -4.4)
Ukraine 803 (724 – 887) Increasing 1.2 (1.1 – 1.3) 14 (11 – 21)
United Arab Emirates 406 (359 – 447) Decreasing 0.9 (0.8 – 1) -30 (-240 – -16)
United Kingdom 1328 (1224 – 1428) Unsure 1 (0.9 – 1) 360 (53 – -74)
United Republic of Tanzania 10 (3 – 15) Decreasing 0.7 (0.4 – 1) -8.4 (31 – -3.7)
United States of America 27470 (25218 – 29964) Increasing 1.1 (1.1 – 1.2) 22 (19 – 27)
Uzbekistan 170 (148 – 193) Increasing 1.1 (1 – 1.3) 21 (11 – 470)
Venezuela 127 (102 – 147) Likely increasing 1.2 (1 – 1.3) 19 (9 – -200)
Yemen 38 (24 – 52) Unsure 1 (0.8 – 1.3) 74 (8.7 – -11)
Zambia 20 (11 – 28) Unsure 0.9 (0.6 – 1.2) -26 (13 – -6.4)
Zimbabwe 23 (11 – 32) Likely increasing 1.2 (0.9 – 1.6) 11 (4.5 – -21)